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Gradual syntactic triggering

The gradient parameter hypothesis

Datos Bibliográficos

ID21630862
AutoresKatherine Howitt (Hunter College, City University of New York), Soumik Dey (Hunter College, City University of New York), William Gregory Sakas (Hunter College, City University of New York, autor de correspondencia)
Año2021
Volumen28
Número1
Páginas65-96
Fecha de publicación2021-01-02
Peer ReviewedSí
Open AccessNo
TipoARTICLE
RevistaLanguage Acquisition (JOURNAL)
Identificadores de la revistaISSN: 1048-9223 • E-ISSN: 1532-7817
EditorialInforma UK Limited (PUBLISHER • GB)
DOI10.1080/10489223.2020.1803329
OpenAlexW3092322361
IdiomaEN
Citas recibidas1
Referencias citadas42

In this article, we propose a reconceptualization of the principles and parameters (P&P) framework. We argue that in lieu of discrete parameter values, a parameter value exists on a gradient plane that encodes a learner’s confidence that a particular parametric structure licenses the utterances in the learner’s linguistic input. Crucially, this gradient parameter hypothesis obviates the need for default parameter values. Default parameter values can be put to use effectively from the perspective of linguistic learnability but are lacking in terms of empirical and theoretical consistency. We present findings from a computational implementation of a gradient P&P learner. The findings suggest that the gradient parameter hypothesis provides the basis for a viable alternative to existing computational models of language acquisition in the classic P&P paradigm. We close with a brief discussion of how a gradient parameter space offers a path to address shortcomings that have been attributed to the P&P framework

Computer Science · Mathematics · Natural Language Processing Techniques · semigroups and automata theory · Syntax, Semantics, Linguistic Variation

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Obras citantes distintas1
Citas por año1
Intervalo de citas2026 - 2026 (1)
Velocidad de citacióncurrent
Altamente citadoNo
Tipos de citaNeutras: 1
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